期刊
DIABETES RESEARCH AND CLINICAL PRACTICE
卷 202, 期 -, 页码 -出版社
ELSEVIER IRELAND LTD
DOI: 10.1016/j.diabres.2023.110772
关键词
Metabolomics; NMR; Machine learning; Lipoproteins; Glycoproteins; Glucose
The aim of this study was to combine nuclear magnetic resonance-based metabolomics and machine learning to identify a glucose-independent molecular signature associated with future type 2 diabetes development. A metabolomic analysis was performed on serum samples from individuals in the Di@bet.es study, revealing lipoprotein and glycoprotein profiles as well as 15 low molecular weight metabolites that were related to the development of type 2 diabetes. Machine learning models also highlighted the roles of inflammation and muscle as independent factors in the development of type 2 diabetes.
Aims: The aim of this study was to combine nuclear magnetic resonance-based metabolomics and machine learning to find a glucose-independent molecular signature associated with future type 2 diabetes mellitus development in a subgroup of individuals from the Di@bet.es study.Methods: The study group included 145 individuals developing type 2 diabetes mellitus during the 8-year followup, 145 individuals matched by age, sex and BMI who did not develop diabetes during the follow-up but had equal glucose concentrations to those who did and 145 controls matched by age and sex. A metabolomic analysis of serum was performed to obtain the lipoprotein and glycoprotein profiles and 15 low molecular weight metabolites. Several machine learning-based models were trained.Results: Logistic regression performed the best classification between individuals developing type 2 diabetes during the follow-up and glucose-matched individuals. The area under the curve was 0.628, and its 95% confidence interval was 0.510-0.746. Glycoprotein-related variables, creatinine, creatine, small HDL particles and the Johnson-Neyman intervals of the interaction of Glyc A and Glyc B were statistically significant.Conclusions: The model highlighted a relevant contribution of inflammation (glycosylation pattern and HDL) and muscle (creatinine and creatine) in the development of type 2 diabetes as independent factors of hyperglycemia.
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